Search results for: Daniel Wang
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1799

Search results for: Daniel Wang

1229 Research on the Public Policy of Vehicle Restriction under Traffic Control

Authors: Wang Qian, Bian Cheng Xiang

Abstract:

In recent years, with the improvement of China's urbanization level, the number of urban motor vehicles has grown rapidly. As residents' daily commuting necessities, cars cause a lot of exhaust emissions and urban traffic congestion. In the "Fourteenth Five Year Plan" of China, it is proposed to strive to reach the peak of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. Urban transport accounts for a high proportion of carbon emission sources. It is an important driving force for the realization of China's carbon peak strategy. Some cities have introduced and implemented the policy of "car restriction" to solve related urban problems by reducing the use of cars. This paper analyzes the implementation of the "automobile restriction" policy, evaluates the relevant effects of the automobile restriction policy, and discusses how to better optimize the "automobile restriction" policy in the process of urban governance.

Keywords: carbon emission, traffic jams, vehicle restrictions, evaluate

Procedia PDF Downloads 151
1228 Factors Influencing University Students' Online Disinhibition Behavior: The Moderating Effects of Deterrence and Social Identity

Authors: Wang, Kuei-Ing, Jou-Fan Shih

Abstract:

This study adopts deterrence theory as well as social identities as moderators, and explores their moderating affects on online toxic disinhibition. Survey and Experimental methodologies are applied to test the research model and four hypotheses are developed in this study. The controllability of identity positively influenced the behavior of toxic disinhibition both in experimental and control groups while the fluidity of the identity did not have significant influences on online disinhibition. Punishment certainty, punishment severity as well as social identity negatively moderated the relation between the controllability of the identity and the toxic disinhibition. The result of this study shows that internet users hide their real identities when they behave inappropriately on internet, but once they acknowledge that the inappropriate behavior will be found and punished severely, the inappropriate behavior then will be weakened.

Keywords: seductive properties of internet, online disinhibition, punishment certainty, punishment severity, social identity

Procedia PDF Downloads 505
1227 Attention-based Adaptive Convolution with Progressive Learning in Speech Enhancement

Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

Abstract:

The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

Procedia PDF Downloads 117
1226 TMIF: Transformer-Based Multi-Modal Interactive Fusion for Rumor Detection

Authors: Jiandong Lv, Xingang Wang, Cuiling Shao

Abstract:

The rapid development of social media platforms has made it one of the important news sources. While it provides people with convenient real-time communication channels, fake news and rumors are also spread rapidly through social media platforms, misleading the public and even causing bad social impact in view of the slow speed and poor consistency of artificial rumor detection. We propose an end-to-end rumor detection model-TIMF, which captures the dependencies between multimodal data based on the interactive attention mechanism, uses a transformer for cross-modal feature sequence mapping and combines hybrid fusion strategies to obtain decision results. This paper verifies two multi-modal rumor detection datasets and proves the superior performance and early detection performance of the proposed model.

Keywords: hybrid fusion, multimodal fusion, rumor detection, social media, transformer

Procedia PDF Downloads 229
1225 Image Reconstruction Method Based on L0 Norm

Authors: Jianhong Xiang, Hao Xiang, Linyu Wang

Abstract:

Compressed sensing (CS) has a wide range of applications in sparse signal reconstruction. Aiming at the problems of low recovery accuracy and long reconstruction time of existing reconstruction algorithms in medical imaging, this paper proposes a corrected smoothing L0 algorithm based on compressed sensing (CSL0). First, an approximate hyperbolic tangent function (AHTF) that is more similar to the L0 norm is proposed to approximate the L0 norm. Secondly, in view of the "sawtooth phenomenon" in the steepest descent method and the problem of sensitivity to the initial value selection in the modified Newton method, the use of the steepest descent method and the modified Newton method are jointly optimized to improve the reconstruction accuracy. Finally, the CSL0 algorithm is simulated on various images. The results show that the algorithm proposed in this paper improves the reconstruction accuracy of the test image by 0-0. 98dB.

Keywords: smoothed L0, compressed sensing, image processing, sparse reconstruction

Procedia PDF Downloads 111
1224 Data-Centric Anomaly Detection with Diffusion Models

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

Abstract:

Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

Procedia PDF Downloads 77
1223 A t-SNE and UMAP Based Neural Network Image Classification Algorithm

Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

Abstract:

Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

Procedia PDF Downloads 190
1222 Effectiveness of Buteyko Method in Asthma Control and Quality of Life of School-Age Children

Authors: Romella C. Lina, Matthew Daniel V. Leysa, Zarah D. F. Libozada, Maria Francesca I. Lirio, Angelo A. Liwag, Gabriel D. Ramos, Margaret M. Natividad

Abstract:

This study aimed to determine the effectiveness of Buteyko Method in asthma control and quality of life of school-age children wherein a pretest-posttest design was utilized to measure the changes after the administration of Buteyko Method. Fourteen (14) subjects with bronchial asthma, aged 7-11 participated in the study. They were equally divided into two groups: the control group received no intervention while the experimental group was asked to attend sessions of Buteyko Method lecture and demonstration. The experimental group was visited for three (3) consecutive weeks to monitor their progress and compliance. Both groups were asked to answer ACQ pre- and post-intervention and PAQLQ before the start of the intervention phase and every week during the follow-up visits. In comparing the asthma control pre-test and post-test mean scores of the control group, no significant difference was noted (p=0.177) while the experimental group showed a significant difference after the administration of Buteyko Method (p=0.002). Moreover, the quality of life pre-test and post-test mean scores of the control group showed no significant difference in any week within one month of follow-up (p=0.736, 0.604, 0.689) while the experimental group showed a significant difference on the third week (p = 0.035) and fourth week (p=0.002) but no significant difference on the second week (p=0.111). Therefore, the use of Buteyko Method within 3-4 weeks as an adjunct to conventional management of asthma helps in improving asthma control and quality of life of school-age children.

Keywords: Buteyko Method, asthma, school-age children, asthma control, quality of life

Procedia PDF Downloads 411
1221 Understanding the Mechanisms of Salmonella typhimurium Resistance to Cannabidiol

Authors: Iddrisu Ibrahim, Joseph Atia Ayariga, Junhuan Xu, Daniel Abugri, Boakai Robertson, Olufemi S. Ajayi

Abstract:

The emergence of multidrug resistance poses a huge risk to public health globally. Yet these recalcitrant pathogens continue to rise in incidence rate, with resistance rates significantly outpacing the speed of antibiotic development. This, therefore, presents an aura of related health issues such as untreatable nosocomial infections arising from organ transplants and surgeries, as well as community-acquired infections that are related to people with compromised immunity, e.g., diabetic and HIV patients, etc. There is a global effort to fight multidrug-resistant pathogens spearheaded by the World Health Organization, thus calling for research into novel antimicrobial agents to fight multiple drug resistance. Previously, our laboratory demonstrated that Cannabidiol (CBD) was an effective antimicrobial against Salmonella typhimurium (S. typhimurium). However, we observed resistance development over time. To understand the mechanisms S. typhimurium uses to develop resistance to Cannabidiol (CBD), we studied the abundance of bacteria lipopolysaccharide (LPS) and membrane sterols of both susceptible and resistant S. typhimurium. Using real-time quantitative polymerase chain reaction (RT-qPCR), we also analyzed the expression of selected genes known for aiding resistance development in S. typhimurium. We discovered that there was a significantly higher expression of blaTEM, fimA, fimZ, and integrons in the CBD-resistant bacteria, and these were also accompanied by a shift in abundance in cell surface molecules such as lipopolysaccharide (LPS) and sterols.

Keywords: antimicrobials, resistance, cannabidiol, gram-negative bacteria, integrons, blaTEM, Fim, LPS, ergosterols

Procedia PDF Downloads 91
1220 A Comparative Analysis of the Performance of COSMO and WRF Models in Quantitative Rainfall Prediction

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

Abstract:

The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

Procedia PDF Downloads 256
1219 Statistical Analysis of Cables in Long-Span Cable-Stayed Bridges

Authors: Ceshi Sun, Yueyu Zhao, Yaobing Zhao, Zhiqiang Wang, Jian Peng, Pengxin Guo

Abstract:

With the rapid development of transportation, there are more than 100 cable-stayed bridges with main span larger than 300 m in China. In order to ascertain the statistical relationships among the design parameters of stay cables and their distribution characteristics, 1500 cables were selected from 25 practical long-span cable-stayed bridges. A new relationship between the first order frequency and the length of cable was found by conducting the curve fitting. Then, based on this relationship other interesting relationships were deduced. Several probability density functions (PDFs) were used to investigate the distributions of the parameters of first order frequency, stress level and the Irvine parameter. It was found that these parameters obey the Lognormal distribution, the Weibull distribution and the generalized Pareto distribution, respectively. Scatter diagrams of the three parameters were plotted and their 95% confidence intervals were also investigated.

Keywords: cable, cable-stayed bridge, long-span, statistical analysis

Procedia PDF Downloads 627
1218 Using Deep Learning for the Detection of Faulty RJ45 Connectors on a Radio Base Station

Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

Abstract:

A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

Procedia PDF Downloads 195
1217 Wear Performance of SLM Fabricated 1.2709 Steel Nanocomposite Reinforced by TiC-WC for Mould and Tooling Applications

Authors: Daniel Ferreira, José M. Marques Oliveira, Filipe Oliveira

Abstract:

Wear phenomena is critical in injection moulding processes, causing failure of the components, and making the parts more expensive with an additional wasting time. When very abrasive materials are being injected inside the steel mould’s cavities, such as polymers reinforced with abrasive fibres, the consequences of the wear are more evident. Maraging steel (1.2709) is commonly employed in moulding components to resist in very aggressive injection conditions. In this work, the wear performance of the SLM produced 1.2709 maraging steel reinforced by ultrafine titanium and tungsten carbide (TiC-WC), was investigated using a pin-on-disk testing apparatus. A polypropylene reinforced with 40 wt.% fibreglass (PP40) disk, was used as the counterpart material. The wear tests were performed at 40 N constant load and 0.4 ms-1 sliding speed at room temperature and humidity conditions. The experimental results demonstrated that the wear rate in the 18Ni300-TiC-WC composite is lower than the unreinforced 18Ni300 matrix. The morphology and chemical composition of the worn surfaces was observed by 3D optical profilometry and scanning electron microscopy (SEM), respectively. The resulting debris, caused by friction, were also analysed by SEM and energy dispersive X-ray spectroscopy (EDS). Their morphology showed distinct shapes and sizes, which indicated that the wear mechanisms, may be different in maraging steel produced by casting and SLM. The coefficient of friction (COF) was recorded during the tests, which helped to elucidate the wear mechanisms involved.

Keywords: selective laser melting, nanocomposites, injection moulding, polypropylene with fibreglass

Procedia PDF Downloads 147
1216 Deposition and Properties of PEO Coatings on Zinc-Aluminum Alloys

Authors: Linlin Wang, Guangdong Bian, Jifeng Shen, Jingzhu Zeng

Abstract:

Zinc-aluminum alloys have been applied as alternatives to bronze, aluminum alloys, and cast iron due to their distinguishing features such as high as-cast strength, excellent bearing properties, as well as low energy requirements for melting. In this study, oxide coatings were produced on ZA27 zinc-aluminum alloy by a plasma electrolytic oxidation (PEO) method. Three coatings were deposited by using three various electrolytes, i.e. silicate, aluminate and aluminate/borate composite solutions. The current density is set at 0.1A/cm2, deposition time is 40 mins for all the deposition processes. The surface morphology and phase structure of the three coatings were characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD). Pin-on-disc sliding wear tests were conducted to test the tribological properties of coatings. The results indicated that the coating produced using the aluminate/borate composite electrolyte had the highest deposition rate and best wear resistance among the three coatings.

Keywords: oxide coating, PEO, tribological properties, ZA27

Procedia PDF Downloads 483
1215 The Micro-Activated Organic Regeneration in Rural Construction: A Case Study of Yangdun Village in Deqing County, Zhejiang Province

Authors: Chengyuan Zhu, Zhu Wang

Abstract:

With the strategy of Rural Rejuvenation proposed in China, the rural has become the focus of all works today. In addition to the support of industry and policy, the rural planning and construction which is the space dependence of Rural Rejuvenation are also very crucial. Based on an analysis of the case of Yangdun Village in Deqing County, this paper summarizes village existing resources and construction status quo. It tries to illuminate the micro-activated organic renewal strategies and methods, based on ecological landscape, history context, industry development and living life requirements. It takes advantage of industrial linkage and then asks for the coordination of both spatial and industrial planning, the revival and remodeling of the rural image can be achieved through shaping the of architectural and landscape nodes as well as the activation of street space.

Keywords: rural construction, rural human settlements, micro-activation, organic renewal

Procedia PDF Downloads 222
1214 Electromagnetic Interference Shielding Effectiveness of a Corrugated Rectangular Waveguide for a Microwave Conveyor-Belt Drier

Authors: Sang-Hyeon Bae, Sung-Yeon Kim, Min-Gyo Jeong, Ji-Hong Kim, Wang-Sang Lee

Abstract:

Traditional heating methods such as electric ovens or steam heating are slow and not very efficient. For continuously heating the objects, a microwave conveyor-belt drier is widely used in the industrial microwave heating systems. However, there is a problem in which electromagnetic wave leaks toward outside of the heating cavity through the insertion opening. To achieve the prevention of the leakage of microwaves and improved heating characteristics, the corrugated rectangular waveguide at the entrance and exit openings of a microwave conveyor-belt drier is proposed and its electromagnetic interference (EMI) shielding effectiveness is analyzed and verified. The corrugated waveguides in the proposed microwave heating system achieve at least 20 dB shielding effectiveness while ensuring a sufficient height of the openings.

Keywords: corrugated, electromagnetic wave, microwave conveyor-belt drier, rectangular waveguide, shielding effectiveness

Procedia PDF Downloads 508
1213 The Performance of Typical Kinds of Coating of Printed Circuit Board under Accelerated Degradation Test

Authors: Xiaohui Wang, Liwei Sun, Guilin Zhang

Abstract:

Printed circuit board (PCB) is the carrier of electronic components. Its coating is the first barrier for protecting itself. If the coating is damaged, the performance of printed circuit board will decrease rapidly until failure. Therefore, the coating plays an important role in the entire printed circuit board. There are common four kinds of coating of printed circuit board that the material of the coatings are paryleneC, acrylic, polyurethane, silicone. In this paper, we designed an accelerated degradation test of humid and heat for these four kinds of coating. And chose insulation resistance, moisture absorption and surface morphology as its test indexes. By comparing the change of insulation resistance of the coating before and after the test, we estimate failure time of these coatings based on the degradation of insulation resistance. Based on the above, we estimate the service life of the four kinds of PCB.

Keywords: printed circuit board, life assessment, insulation resistance, coating material

Procedia PDF Downloads 526
1212 Modeling of Crack Propagation Path in Concrete with Coarse Trapezoidal Aggregates by Boundary Element Method

Authors: Chong Wang, Alexandre Urbano Hoffmann

Abstract:

Interaction between a crack and a trapezoidal aggregate in a single edge notched concrete beam is simulated using boundary element method with an automatic crack extension program. The stress intensity factors of the growing crack are obtained from the J-integral. Three crack extension paths: deflecting around the particulate, growing along the interface and penetrating into the particulate are achieved in terms of the mismatch state of mechanical characteristics of matrix and the particulate. The toughening is also given by the ratio of stress intensity factors. The results reveal that as stress shielding occurs, toughening is obtained when the crack is approaching to a stiff and strong aggregate weakly bonded to a relatively soft matrix. The present work intends to help for the design of aggregate reinforced concretes.

Keywords: aggregate concrete, boundary element method, two-phase composite, crack extension path, crack/particulate interaction

Procedia PDF Downloads 422
1211 Sparse Signal Restoration Algorithm Based on Piecewise Adaptive Backtracking Orthogonal Least Squares

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

Abstract:

the traditional greedy compressed sensing algorithm needs to know the signal sparsity when recovering the signal, but the signal sparsity in the practical application can not be obtained as a priori information, and the recovery accuracy is low, which does not meet the needs of practical application. To solve this problem, this paper puts forward Piecewise adaptive backtracking orthogonal least squares algorithm. The algorithm is divided into two stages. In the first stage, the sparsity pre-estimation strategy is adopted, which can quickly approach the real sparsity and reduce time consumption. In the second stage iteration, the correction strategy and adaptive step size are used to accurately estimate the sparsity, and the backtracking idea is introduced to improve the accuracy of signal recovery. Through experimental simulation, the algorithm can accurately recover the estimated signal with fewer iterations when the sparsity is unknown.

Keywords: compressed sensing, greedy algorithm, least square method, adaptive reconstruction

Procedia PDF Downloads 139
1210 Positive Bias and Length Bias in Deep Neural Networks for Premises Selection

Authors: Jiaqi Huang, Yuheng Wang

Abstract:

Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

Procedia PDF Downloads 176
1209 Team Teaching, Students Perception, Challenges, and Remedies for Effective Implementation: A Case Study of the Department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria

Authors: Daniel Ihemtuge Akim, Micheal O. Ikeanumba

Abstract:

This research focused on team teaching; students perception, challenges, and remedies for effective implementation, a case study of the department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria. It seeks to address the misconception by students on the use of team teaching as a methodology for learning. Five purposes and five research questions guided this study. Descriptive survey design was used in the study. The students of biology department enrolled in both Bachelor degree and National Certificate in Education in Alvan Ikoku Federal College of Education, Owerri, formed the population size. Simple random sampling technique was used to select the sampled students and 20% of whole lecturers were selected out of the whole given sample size of three hundred and forty (340). The instrument used for data collection was structured 4 point Likert scale questionnaire and analysis was made using mean method. The result revealed that poor time management by lectures, lack of lecture venues, manpower are some of the challenges hindering the effective implementation of team teaching. It was also observed that students perform better in academic when team teaching approach is used than single teaching approach. Finally, recommendations made suggested that teachers involved in team teaching should work together with their teaching strategies and within the time frame to achieve the stated objectives.

Keywords: challenges, implementation, perception, team teaching

Procedia PDF Downloads 376
1208 Hidden Populations and Women: New Political, Methodological and Ethical Challenges

Authors: Renée Fregosi

Abstract:

The contribution presently proposed will report on the beginnings of a Franco-Chilean study to be launched in 2015 by a multidisciplinary team of Renée Fregosi Political Science University Paris 3 / CECIEC, Norma Muñoz Public Policies University of Santiago of Chile, Jean-Daniel Lelievre, Medicine Paris 11 University, Marcelo WOLFF Medicine University of Chile, Cecilia Blatrix Political Science University Paris-Tech, Ernesto OTTONE, Political Science University of Chile, Paul DENY Medicine Paris 13 University, Rafael Bugueno Medicine Hospital Urgencia Pública of Santiago, Eduardo CARRASCO Political Science Paris 3 University. The problem of hidden populations challenges some criteria and concepts to re-examine: in particular the concept of target population, sampling methods to "snowball" and the cost-effectiveness criterion that shows the connection of political and scientific fields. Furthermore, if the pattern of homosexual transmission still makes up the highest percentage of the modes of infection with HIV, there is a continuous increase in the number of people infected through heterosexual sex, including women and persons aged 50 years and older. This group can be described as " unknown risk people." Access to these populations is a major challenge and raises methodological, ethical and political issues of prevention, particularly on the issue of screening. This paper proposes an inventory of these types of problems and their articulation, to define a new phase in the prevention against HIV refocused on women.

Keywords: HIV testing, hidden populations, difficult to reach PLWHA, women, unknown risk people

Procedia PDF Downloads 518
1207 Phase II Monitoring of First-Order Autocorrelated General Linear Profiles

Authors: Yihua Wang, Yunru Lai

Abstract:

Statistical process control has been successfully applied in a variety of industries. In some applications, the quality of a process or product is better characterized and summarized by a functional relationship between a response variable and one or more explanatory variables. A collection of this type of data is called a profile. Profile monitoring is used to understand and check the stability of this relationship or curve over time. The independent assumption for the error term is commonly used in the existing profile monitoring studies. However, in many applications, the profile data show correlations over time. Therefore, we focus on a general linear regression model with a first-order autocorrelation between profiles in this study. We propose an exponentially weighted moving average charting scheme to monitor this type of profile. The simulation study shows that our proposed methods outperform the existing schemes based on the average run length criterion.

Keywords: autocorrelation, EWMA control chart, general linear regression model, profile monitoring

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1206 Titanium-Aluminium Oxide Coating on Aluminized Steel

Authors: Fuyan Sun, Guang Wang, Xueyuan Nie

Abstract:

In this study, a plasma electrolytic oxidation (PEO) process was used to form titanium-aluminium oxide coating on aluminized steel. The present work was mainly to study the effects of treatment time of PEO process on properties of the titanium coating. A potentiodynamic polarization corrosion test was employed to investigate the corrosion resistance of the coating. The friction coefficient and wear resistance of the coating were studied by using pin-on-disc test. The thermal transfer behaviours of uncoated and PEO-coated aluminized steels were also studied. It could be seen that treatment time of PEO process significantly influenced the properties of the titanium oxide coating. Samples with a longer treatment time had a better performance for corrosion and wear protection. This paper demonstrated different treatment time could alter the surface behaviour of the coating material.

Keywords: titanium-aluminum oxide, plasma electrolytic oxidation, corrosion, wear, thermal property

Procedia PDF Downloads 351
1205 Automated Driving Deep Neural Networks Model Accuracy and Performance Assessment in a Simulated Environment

Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

Abstract:

The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of the Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling human behavior. However, the exclusive use of this technology still seems insufficient to control vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: accuracy assessment, AI-driven mobility, artificial intelligence, automated vehicles

Procedia PDF Downloads 106
1204 Enhancing goal Achivement through Improved Communication Skills

Authors: Lin Xie, Yang Wang

Abstract:

An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning 2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: communication, education, language learning, goal achievement, academic success

Procedia PDF Downloads 62
1203 The Impact of the “Cold Ambient Color = Healthy” Intuition on Consumer Food Choice

Authors: Yining Yu, Bingjie Li, Miaolei Jia, Lei Wang

Abstract:

Ambient color temperature is one of the most ubiquitous factors in retailing. However, there is limited research regarding the effect of cold versus warm ambient color on consumers’ food consumption. This research investigates an unexplored lay belief named the “cold ambient color = healthy” intuition and its impact on food choice. We demonstrate that consumers have built the “cold ambient color = healthy” intuition, such that they infer that a restaurant with a cold-colored ambiance is more likely to sell healthy food than a warm-colored restaurant. This deep-seated intuition also guides consumers’ food choices. We find that using a cold (vs. warm) ambient color increases the choice of healthy food, which offers insights into healthy diet promotion for retailers and policymakers. Theoretically, our work contributes to the literature on color psychology, sensory marketing, and food consumption.

Keywords: ambient color temperature, cold ambient color, food choice, consumer wellbeing

Procedia PDF Downloads 131
1202 The Strategy of Traditional Religious Culture Tourism: Taking Taiwan Minhsiung Infernal Lord Festival for Example

Authors: Ching-Yi Wang

Abstract:

The purpose of this study is to explore strategies for integrate Minhsiung environments and cultural resources for Infernal Lord Festival. Minhsiung Infernal Lord Festival is one of the famous religious event in Chia-Yi County, Taiwan. This religious event and the life of local residents are inseparable. Minhsiung Infernal Lord Festival has a rich cultural ceremonies meaning and sentiment of local concern. This study apply field study, document analysis and interviews to analyze Minhsiung Township’s featured attractions and folklore events. The research results reveal the difficulties and strategies while incorporating culture elements into culture tourism. This study hopes to provide innovative techniques for the purpose of prolonging the feasibility of future development of the tradition folk culture.

Keywords: Taiwan folk culture, Minhsiung Infernal Lord Festival, religious tourism, folklore, cultural tourism

Procedia PDF Downloads 338
1201 Research and Application of the Three-Dimensional Visualization Geological Modeling of Mine

Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao

Abstract:

Today's mining industry is advancing gradually toward digital and visual direction. The three dimensional visualization geological modeling of mine is the digital characterization of mineral deposit, and is one of the key technology of digital mine. The three-dimensional geological modeling is a technology that combines the geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in three-dimensional environment with computer technology, and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provided scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

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1200 Exploring Alignability Effects and the Role of Information Structure in Promoting Uptake of Energy Efficient Technologies

Authors: Rebecca Hafner, David Elmes, Daniel Read

Abstract:

The current research applies decision-making theory to the problem of increasing uptake of energy efficient technologies in the market place, where uptake is currently slower than one might predict following rational choice models. We apply the alignable/non-alignable features effect and explore the impact of varying information structure on the consumers’ preference for standard versus energy efficient technologies. In two studies we present participants with a choice between similar (boiler vs. boiler) vs. dissimilar (boiler vs. heat pump) technologies, described by a list of alignable and non-alignable attributes. In study One there is a preference for alignability when options are similar; an effect mediated by an increased tendency to infer missing information is the same. No effects of alignability on preference are found when options differ. One explanation for this split-shift in attentional focus is a change in construal levels potentially induced by the added consideration of environmental concern. Study two was designed to explore the interplay between alignability and construal level in greater detail. We manipulated construal level via a thought prime task prior to taking part in the same heating systems choice task, and find that there is a general preference for non-alignability, regardless of option type. We draw theoretical and applied implications for the type of information structure best suited for the promotion of energy efficient technologies.

Keywords: alignability effects, decision making, energy-efficient technologies, sustainable behaviour change

Procedia PDF Downloads 304